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PubMed2026

Genetic mutations driving ciprofloxacin resistance in laboratory-evolved Salmonella Typhimurium.

Ciprofloxacin resistance in Salmonella Typhimurium is a significant public health concern, and the mechanisms by which the resistance evolves are poorly defined. Here, by serial passaging under antibiotic selection, we isolated ciprofloxacin-resistant S. Typhimurium mutants and subjected them to whole-genome sequencing to reveal the major mutations associated with resistance. The Low CipR mutant acquired four chromosomal mutations in ramR, icdA, lipB, and gyrA, and the High CipR mutant gained additional mutations in gyrB, yaiC, and corA. Functional characterization determined that mutations in ramR resulted in efflux pump upregulation, while disruptions in the TCA cycle caused by mutations in icdA and lipB led to metabolic alterations. These changes indirectly enhanced resistance by increasing the expression of the global regulator MarA and reducing OmpF-dependent membrane permeability. Despite the observation of the G105A substitution in GyrA, enzymatic assays confirmed the failure to support resistance to ciprofloxacin, possibly because the structural alteration remained minimal. GyrB488-489dup was associated with maintained supercoiling under ciprofloxacin and enhanced fluoroquinolone resistance, suggesting a major role in resistance evolution. Other mutations in yaiC impaired biofilm and, in corA, intracellular accumulation of magnesium, possibly stabilizing the bacterial cell envelope under antibiotic pressure. The findings provide novel explanations for the multifaceted mechanisms leading to ciprofloxacin resistance in Salmonella and suggest targets to combat antimicrobial resistance.IMPORTANCEAntibiotic resistance in Salmonella Typhimurium is an increasing public health concern, yet the genetic changes that allow bacteria to become resistant are not fully understood. In this study, we evolved ciprofloxacin-resistant Salmonella in the laboratory and identified the mutations that arise during resistance development. We found that resistance does not result from a single change but from multiple adaptations affecting drug efflux, metabolism, and the antibiotic target. Some mutations increased the activity of pumps that remove antibiotics from the cell, while others altered bacterial metabolism and reduced membrane permeability, making it harder for the drug to enter. A duplication in the DNA gyrase subunit GyrB played a particularly important role in maintaining DNA function under antibiotic stress. Together, these results reveal how diverse genetic changes cooperate to generate ciprofloxacin resistance and provide insights that may help guide strategies to combat drug-resistant Salmonella infections.

DNA gyrase↗
PubMed2026

Temporal shifts in gyrA mutation types and sublineage replacement in ST11 Salmonella enterica serovar Enteritidis over a decade (2014-2023): A genomic epidemiological study in Guangxi, China.

The overuse or abuse of antibiotics drives the global health threat of antimicrobial resistance. Although bans on certain veterinary antibiotics, such as colistin, have proven effective, the impact of fluoroquinolone stewardship on the evolution of the foodborne pathogen Salmonella enterica serovar Enteritidis (S. Enteritidis) remains unclear. Here, we conducted a decade-long (2014-2023) retrospective longitudinal genomic epidemiological analysis of 441 ST11 S. Enteritidis isolates from Guangxi, China, alongside a global reference dataset of 4297 genomes. Our aim was to elucidate the effect of real-world antibiotic stewardship on the shift of gyrA point mutations and lineage distribution. Surveillance identified three global epidemic clade sublineages (GEC-L2, L3, L4), with the multidrug-resistant GEC-L4 (i.e., GC-c or MMC2), characterized by the gyrA mutation with amino acid substitution D87Y, being domestically dominant (70.07%, 309/441). Following China's 2016 ban on the veterinary use of critical fluoroquinolones, the proportion of the highly resistant GEC-L4 sublineage decreased continuously (from 86.84% in 2017 to 56.00% in 2023), while the less resistant GEC-L3 sublineage (i.e., GC-b or MMC1), mainly characterized by gyrA D87G, increased simultaneously (from 13.16% to 44.00%). This phenomenon might be attributed to the fact that the GEC-L4 sublineage exhibited a higher fitness cost compared with the GEC-L3 sublineage, as confirmed by the competition assay. A Random Forest Model validated that the gyrA mutation with amino acid substitution D87Y was the paramount feature for these sublineages' identification. In contrast, global data showed a continuous increase in gyrA mutations (from 8.63% in 2006 to 68.85% in 2024), primarily D87Y (from 1.44% to 31.15%) and D87N (from 4.32% to 22.95%), correlating with rising average fluoroquinolone consumption. This study provides direct genomic evidence that national-level antibiotic stewardship can drive the replacement of highly resistant sublineages with moderately resistant ones. These findings offer crucial scientific evidence for evaluating the impact of antibiotic management policies and inform strategies for the rational use of antimicrobials.

China↗
PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗
PubMed2026

Trade-offs in avian parental care: a review of theory and meta-analysis of brood size manipulations.

The selective forces shaping parental care have been studied for over 50 years. While theoretical and experimental work has yielded qualitative progress, the large body of empirical work testing predictions about parental investment based on life-history trade-offs has yet to be synthesized. We first provide an overview of the core life-history theory exploring how selection might shape parental care. We then conduct a systematic review and meta-analysis on studies that experimentally manipulated brood size in birds, a widely used experimental approach to manipulate parental investment. We extracted 313 estimates from 62 studies representing 31 species of birds from 19 different families and tested key predictions on trade-offs in parental care derived from theory. Our analysis provides strong support for some predictions about life-history trade-offs in parental care, but weak or equivocal support for others. Specifically, we found that overall, avian parents respond to brood size manipulations as predicted by life-history theory: they increased care in response to brood enlargement, and decreased care in response to brood reductions. Furthermore, for the same relative manipulation size, responses to brood reductions were greater than responses to brood enlargements. This finding is consistent with predictions derived from life-history theory based on some types of non-linear utility curves. However, many predictions derived from theory are not well supported by our comparative analysis. Species' life-history traits such as clutch size (a measure of current reproduction), adult survival, and broods per year (two measures of future reproduction), explained little, if any, among-species variation in response to brood size manipulations. Several factors may explain this. We highlight that brood size manipulations may affect more than just perception of the value of current reproduction, such as altering parents' perception of predation risk. Importantly, these unintended consequences could lead to asymmetric responses like those we observed. Other common experimental approaches - such as hormone manipulations, altering a partner's effort, and food supplementation - often affect multiple traits or fitness components simultaneously, or may involve cues that poorly match the evolved mechanisms guiding parental behaviour. Our review of both theory and experimental approaches suggests that there are multiple opportunities for more precise experiments. We offer several recommendations for effective designs. One is improved understanding of the biology underlying the functions relating to costs and benefits, with careful consideration of not only how the manipulation will affect only one of those, but also the mechanisms that might alter how parents perceive the manipulation. We also emphasize general principles, such as assessing alternative hypotheses and devising multiple independent tests. Armed with these recommendations, we believe there are new opportunities to increase the strength of inference achieved from studies aimed at understanding the trade-offs affecting the evolution of parental care.

Animals↗